A fully integrated system for the automatic detection and characterization of cracks in road flexible pavement surfaces, which does not require manually labeled samples, is proposed to minimize the human subjectivity resulting from traditional visual surveys. The first task addressed, i.e., crack detection, is based on a learning from samples paradigm, where a subset of the available image database is automatically selected and used for unsupervised training of the system. The system classifies nonoverlapping image blocks as either containing crack pixels or not. The second task deals with crack type characterization, for which another classification system is constructed, to characterize the detected cracks' connect components. Cracks are labeled according to the types defined in the Portuguese Distress Catalog, with each different crack present in a given image receiving the appropriate label. Moreover, a novel methodology for the assignment of crack severity levels is introduced, computing an estimate for the width of each detected crack. Experimental crack detection and characterization results are presented based on images captured during a visual road pavement surface survey over Portuguese roads, with promising results. This is shown by the quantitative evaluation methodology introduced for the evaluation of this type of system, including a comparison with human experts' manual labeling results.

IEEE International Conference on Image Processing: Paris: oct. 27-30, 2014This paper presents a comprehensive set of image processing algorithms for detection and characterization of road pavement surface crack distresses, which is being made available to the research community. The toolbox, in the Matlab environment, includes algorithms to preprocess images, to detect cracks and characterize them into types, based on image processing and pattern recognition techniques, as well as modules devoted to the performance evaluation of crack detection and characterization solutions. A sample database of 84 pavement surface images taken during a traditional road survey is provided with the toolbox, since no pavement image databases are publicly available for crack detection and characterization evaluation purposes. Results achieved applying the proposed toolbox to the sample database are discussed, illustrating the potential of the available algorithms

Background: The goal of this article was to research the psychometric properties of the WHOQOL-BREF(PT) instrument in a sample of elderly citizens residing in a rural area in their own homes or at family members’ or friends’ homes and to compare the results: (i) to those reported by the team of Portuguese researchers that undertaken the instrument's translation/validation to the Portuguese language and (ii) to those reported internationally by the World Health Organization Quality of Life group. An overall quality of life scoring (QOL₂₄—all facets) is also proposed in this article as novelty. The correlation level between QOL₂₄ and the instrument’s general facet was also investigated. Methods: This was a cross-sectional study with a sample of 351 elderly citizens (46.4% males and 53.6% females) randomly selected from the official dataset of the Local Health Unit of Baixo Alentejo. All the data were collected by health professionals at the participants’ homes following the structured interview methodology and using the WHOQOL-BREF(PT) instrument. Three different structural equation models were developed: (i) a first-order confirmatory factor analysis, to assess the instrument’s psychometric properties; (ii) a hierarchical second-order confirmatory factor analysis model, to allow determining the QOL₂₄ scoring; and (iii) a more generic structural equation model, to investigate the correlation level between QOL₂₄ and the instrument’s general facet. Results: The WHOQOL-BREF(PT) showed an “almost very good” goodness of fit (comparative fit index of 0.949 and Tucker-Lewis index of 0.943), an adequate internal consistency (Cronbach’s alpha: from 0.64 to 0.90; composite reliability: from 0.59 to 0.88) and tolerable convergent validity (average variance extracted: from 0.374 to 0.614). However, discriminant validity was not reached because strong correlations between the first-order factors (four QOL domains) were obtained, together with low values of the average variance extracted. The scoring of QOL domains and QOL₂₄, determined as weighted averages (proposed in this article as novelty) were significantly different than those determined as unweighted averages. The standardized correlation coefficient between QOL₂₄ and the instrument’s general facet was of 0.89 (statistically highly significant). Conclusions: The WHOQOL-BREF(PT) is a psychometrically sound instrument to assess the QOL of the considered population sample. However, the QOL domains were found strongly intertwined. More studies are necessary to validate the weighted average scoring strategy of QOL domains and QOL₂₄. Concurrent validity between QOL₂₄ and the instrument’s general facet was considered as “strong”.

A core set of International Classification of Functioning, Disability and Health codes was used to ascertain general profiles of functionality as a function of biological and sociodemographic characteristics and to develop structured nursing interventions in accordance with self care deficits identified by studying self care behavior for elderly people living in both extensively and sparsely populated rural areas. Data were collected by health professionals in the participants’ houses. An exploratory factor analysis enabled reduced data dimensions, and factorial validity was assessed by a confirmatory factor analysis. An ordinal regression model was built to identify general profiles of functionality as a function of age. A bar graph was used as a measurement tool for nursing care needs as a function of self care behavior and functional profile level. No functional problems were expected among people under the age of 74 years, while mild functionality problems were expected among people older than 74 years. Regarding nursing care needs, the results of the constructed model suggested that the functional concept “Support and Relationships” is associated with higher levels of functional problems and thus a greater need for self care interventions and that people aged 85 years and older always show therapeutic self care deficits.

The functioning and cognition of older adults can be influenced by different care contexts. We aimed to compare the functioning profiles and cognition of institutionalized and noninstitutionalized older adults and to evaluate the effect of sociodemographic factors on the functioning and cognition. This is a cross-sectional study that included 593 older adults. The data were collected using the Elderly Nursing Core Set and Mini Mental State Examination. Women, older adults who did not attend school and those live in Residential Homes are more likely to have a higher degree of cognitive impairment than men, those who attended school and those frequent Day Centre. The chances of an older adult with moderate or severe cognitive impairment increases with age. Older women, older adults who did not attend school, and older adults who live in Residential Homes had a higher degree of functional problem than men, those who attended school and those who frequent a Day Centre, independently to age. It is necessary to promote the health literacy of older adults throughout life. The implementation of social and health responses should allow older adults to remain in their homes, given the influence of functioning and cognition on self-care and quality of life.